PSYC 523: Statistics and Research Methods Flashcards

1
Q

ANOVA

A

ANOVA stands for “analysis of variance” and it is a statistical procedure used in inferential statistics. ANOVAs test for significant differences among 2+ groups as well and main/interaction effects of the independent variable on the dependent variable.

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2
Q

Clinical vs. Statistical Significance

A

Clinical significance refers to when the results of a study are judged to be meaningful in relation to the diagnoses or treatments of disorders. Statistical significance refers to the actual results of the statistical analyses that aren’t attributed to the operation of chance or random factors.

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3
Q

Construct Validity

A

The degree to which a test or instrument is capable of measuring a concept, trait, or other theoretical entity. How well the variables in a study are defined, measured, or manipulated. The two main types of construct validity found in social science research are convergent validity, how well the measure correlates with other well-established measures of the same construct, and discriminant validity, how much the measure does not correlate with unrelated measures. A test should have both convergent and discriminant validity in order to have high construct validity.

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4
Q

Content Validity

A

The extent to which a test measures all facets of the subject matter or behavior that’s being studied. Content validity cannot be measured empirically/statistically, but rather is assessed through logical analysis.

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5
Q

Correlation vs. Causation

A

Correlation describes a relationship, either positive or negative, between variables. Causation refers to when changes in one variables bring about change in the other variable(s) (i.e. a cause and effect). A correlation is necessary to establish a causal relationship and only experimental studies can establish causal relationships.

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6
Q

Correlational Research

A

A type of research design in which relationships between variables are simply observed without any control over the setting in which those relationships occur. Correlational research does not contain any intentional manipulation of variables by the researcher. The correlation coefficient can range from -1.0 to 1.0 and describes the strength of the relationship, either in a positive or negative direction.

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7
Q

Cross-Sectional Design

A

A research design in which groups, who differ by one key characteristic (i.e. age or developmental level), are compared at a single point in time. A cross-sectional design is typically used to determine the prevalence of a condition.

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8
Q

Dependent t-test

A

This type of statistical procedure compares the means of two related groups to determine whether or not there is a statistically significant difference between those means.

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9
Q

Descriptive vs. Inferential

A

Descriptive statistics depict the main aspects of the sample data without inferring to a larger population (i.e. mean, media, mode, range, standard deviation within the sample). Inferential statistics all inferences about characteristics of a population to be drawn from a sample of data from that population, while controlling for error as much as possible.

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10
Q

Double-Blind Study

A

A type of research design in which neither the participants nor the researcher knows which treatment/intervention participants are receiving until the study is complete. A double-blind study eliminates the possibility of researcher bias toward a participant or group.

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11
Q

Ecological Validity

A

This refers to the degree to which results obtained from research are representative of conditions in the wider world. Research designs with higher ecological validity are assumed to be more generalizable in life outside the confines of research/treatment.

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12
Q

Effect Size

A

Effect size refers to the magnitude or meaningfulness of a relationship between two variables. The larger the effect size, the stronger the phenomenon. This is interpreted as indicating the practical significance of a research finding.

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13
Q

Experimental Research

A

This is a research design that utilizes randomized assignment of participants and a systematic manipulation of variables, while all other variables are, attempted to be, controlled. The objective of experimental research is to draw a causal inference (i.e. any change in the dependent variable was due to the manipulation of the independent variable).

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14
Q

Hypothesis

A

This is an empirically testable proposition about some fact, behavior, or relationship that is usually based on theory. The hypothesis states the expected outcome that will result from the research design’s conditions or assumptions.

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15
Q

Independent t-test

A

This type of statistical procedure compares the means of two independent groups in order to determine if the means are statistically different.

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16
Q

Internal Consistency

A

The degree of interrelationship or homogeneity among the items on a test, such that they are consistent with another and measuring for the same construct. This is tested by dividing the items in half and scoring them separately, then correlating the two halves to check for the degree of consistency.

17
Q

Internal Validity

A

The degree to which a research study is free from flaws in its internal structure (i.e. lack of confounding variables). If so, this means the observed relationship between variables in the study is reflective of the actual relationship between the variables.

18
Q

Interrater Reliability

A

The extent to which independent evaluators produce similar ratings from the same target person or object. Interrater reliability is typically used with more subjective measures to ensure the soundness of the operational definition(s) of the variable(s) in a study.

19
Q

Measures of Central Tendency

A

This refers to values that attempt to describe a set of data by identifying the central position within the set of data. The three main measures of central tendency include the data set’s mean, median, and mode.

20
Q

Nominal, Ordinal, Interval, Ratio Measurements

A

These are four types of scales of measurement used in statistics. Nominal measurements are used for categorical data, ordinal measurements are used for data that is ranked by individual or variable, interval measurements are used for measuring the degree of difference between values when an “absolute zero” is not possible, and ratio measurements are used for measuring the degree of data when an “absolute zero” is possible.

21
Q

Normal Curve

A

A theoretical distribution in which values pile up in the center at the mean, median, and mode value and fall off into “tails” at either end of the distribution. A normal curve produces the familiar “bell-shape” when plotted.

22
Q

Probability

A

This refers to the degree to which an event is likely to occur in a randomly sampled population. As the probability, or p-values, increases it becomes more likely that the result occurred due to chance as opposed to experimental manipulation.

23
Q

Parametric vs. Nonparametric Statistical Analyses

A

Parametric statistical analyses are based on assumptions about the distribution of variables in the population that are being tested. Nonparametric statistical analyses are used when the data being analyzed is such that certain common assumptions about the distribution of variables in the population are not necessary or applicable. Parametric statistics are typically preferred as they are more likely to detect statistical significance than nonparametric statistics.

24
Q

Quasi-Experimental Research

A

A non-experimental research design in which the researcher cannot randomly assign participants to conditions, cannot generally control or manipulate the independent variable, and cannot limit the influence of extraneous variables.

25
Q

Random Sampling

A

A process for selecting a sample of study participants from a larger potential group of eligible individuals. Each person has the same fixed probability of being included in the sample and some chance procedure is used to determine who specifically is chosen for the sample.

26
Q

Regression

A

A statistical technique that’s used to determine how a variable of interest (i.e. the dependent variable) is affected by one or more independent variables. A regression is typically used to predict values or estimate the effect of some exploratory variable on the dependent variable.

27
Q

Sample vs. Population

A

A population is the entire group that a researcher wants to draw conclusions about, whereas the sample is a smaller subset of that population that the researcher collects data from.

28
Q

Scientific Methodology

A

The scientific methodology is used to conduct research in standardized way of making observations, gathering data, forming theories, testing hypotheses, and interpreting results.

29
Q

Standardization Sample

A

A population of individuals who have previously well-documented intelligence and/or achievement levels that are used to ‘standardize’ a new or revised instrument. This is to assure that the new or revised measure is reliably measuring what it is intended to measure.

30
Q

Statistical Significance

A

The degree to which a result cannot be reasonably attributed to chance or random factors. The result is measurably meaningly and the null hypothesis is rejected.

31
Q

Type I and Type II Error

A

A Type I error occurs when the research results reject the null hypothesis when it is in fact true (i.e. false positive). A Type II error occurs when the research fails to reject the null hypothesis when it is in fact not true (i.e. false negative).